Measurement Of Parameters Research Articles

MiR-92b-3p protects retinal tissues against DNA damage and apoptosis by targeting BTG2 in experimental myopia

BackgroundMyopia is one of the eye diseases that can damage the vision of young people. This study aimed to explore the protective role of miR-92b-3p against DNA damage and apoptosis in retinal tissues of negative lens-induced myopic (LIM) guinea pigs by targeting BTG2.MethodsBiometric measurements of ocular parameters, flash electroretinogram (FERG), and retinal thickness (RT) were performed after miR-92b-3p intravitreal injection in LIM guinea pigs. The apoptotic rate was detected by Annexin V-FITC/PI double staining, and the change in mitochondrial membrane potential was measured by JC-1 staining. Retinal apoptosis and expression of p53, BTG2, and CDK2 were explored by TdT-mediated dUTP-biotin nick labeling (TUNEL) and immunofluorescence staining assays, respectively. BTG2 and its upstream and downstream molecules at gene and protein levels in retinal tissues were measured by real-time quantitative PCR (qPCR) and Western blotting.ResultsCompared with normal controls (NC), the ocular axial length of LIM guinea pig significantly increased, whereas refraction decreased. Meanwhile, dMax-a and -b wave amplitudes of ERG declined, retinal thickness was decreased, the number of apoptotic cells and apoptotic rate in LIM eyes was exaggerated, and the mitochondrial membrane potential significantly decreased. In addition, results of qPCR and Western blot assays showed that the expression levels of p53, BTG2, CDK2, and BAX in LIM guinea pigs were higher than the levels of the NC group, whereas the BCL-2 expression level was decreased. By contrast, the miR-92b-3p intravitreal injection in LIM guinea pigs could significantly inhibit axial elongation, alleviate DNA damage and apoptosis, and thus protect guinea pigs against myopia.ConclusionIn conclusion, p53 and BTG2 were activated in the retinal tissue of myopic guinea pigs, and the activated BTG2 could elevate the expression of CDK2 and BAX, and attenuate the expression of BCL-2, which in turn promote apoptosis and eventually lead to retinal thinning and impaired visual function in myopic guinea pigs. The miR-92b-3p intravitreal injection can attenuate the elongation of ocular length and retinal thickness, and inhibit the CDK2, BAX, and p53 expression by targeting BTG2, thereby ameliorating DNA damage and apoptosis in LIM guinea pigs and protecting ocular tissues.Graphical

Characterization of the MSAP Flap in Head and Neck Surgical Oncology: A 3D Cadaveric Study.

The medial sural artery (MSA) perforator flap is a versatile free flap. However, the cutaneous perforators are not well characterized. The objectives of this pilot anatomical study were to: (1) visualize in three-dimensions, as in-situ, the origin, course, and distribution of the cutaneous perforators, (2) characterize the number and frequency of the perforators, and (3) quantify mean pedicle length. Thirteen cadaveric specimens were dissected, digitized, and modeled in 3D. Three-dimensional models and dissection photographs were used to determine the origin, course, number, distribution, and pedicle length of MSA perforators. The most common pattern consisted of three perforators (39% of specimens). The maximum number of perforators identified was four (23%). The majority of specimens (92%) had a cutaneous perforator originating from the lateral branch of the MSA and coursed most frequently in the second (43%) and third (37%) quartiles of the length of the tibia. Mean pedicle length was 19.1 ± 6.9 cm. Perforators originating from the medial branch of the MSA were significantly (p < 0.05) shorter than those from the lateral branch and were found to course only in the first quartile. The 3D models constructed in this study provide a comprehensive overview of the location and course of the perforators, enabling measurement of parameters in 3D-space. Anatomical characterization of the MSA perforator flap using 3D analysis can assist reconstructive surgeons in understanding the relevant anatomy and optimizing the surgical technique for flap harvest. N/A Laryngoscope, 2024.

Improving the effectiveness of the DiagBelt+ diagnostic system - analysis of the impact of measurement parameters on the quality of signals

Faults in steel cords in the core are not visible during routine visual inspections. They can be identified using magnetic diagnostic systems. The article presents an analysis of the impact of the sensitivity threshold of the DiagBelt+ system, the diameter of cords in the core, and the belt speed on the quality of signals representing known damage: cutting of cords, their absence, and a reduction in the cross-section of the cord. The study focused on defects to cords across the belt, as they can weaken the belt's strength and lead to a complete belt failure. The proposed results and analyses contribute to the improvement of the methodology for magnetic examination of the core's condition and the developed diagnostic system DiagBelt+. Consequently, this enhances the reliability and safety of belt conveyors in various industries, including in brown coal mines, where it has been implemented (PGE GiEK SA KWB O/Bełchatów), as well as in coal, limestone, and copper ore mines, where it is used to assess the condition of belts with steel cords.

Water Quality from Natural Sources for Sustainable Agricultural Development Strategies: Galapagos, Ecuador

Water is an essential element for agricultural sustainability. In volcanic islands, freshwater sources are limited, challenging the local farming water supply. Rainfall dependence in the Galapagos Islands limits continuous agriculture, and despite using natural water sources, their irrigation quality is little known. This study aimed to carry out a control–diagnosis of irrigation water quality of the natural sources of the four agrarian islands of the Galapagos, considering water quality parameters for the proposal of sustainability strategies in the water and agricultural context. The workflow included (i) freshwater supply situation diagnosis, (ii) physicochemical parameters measurement and hydrochemical characterisation, and (iii) irrigation analysis and sustainability strategies configuration. Results indicated that of the 34 sources analysed, 55.88% are suitable for irrigation and are located in San Cristobal and Santa Cruz. The remaining 44.12% showed problems with parameters such as faecal coliforms, salinity, metals, carbonates, BOD5, and COD above the national permitted limits. Six strategies for water and agricultural sustainability are proposed, including periodic water monitoring, academy–government–community projects, community water board creation, water sowing and harvesting systems, effective management of effluent, and agricultural strengthening. The study guides comprehensive hydric management initiatives to benefit agrarian development and food security, aligning with SDGs 2 and 6.

An inversion method for calculating formation and borehole parameters in X-ray lithology density logging

The use of X-ray sources in place of the 137Cs sources used in traditional lithology density logging methods has become a new trend in the development of nuclear logging techniques. How to eliminate the effects of drilling fluids or mudcake in the measurement process is a key question that determines the accuracy of measurement. In order to reduce the effects of mudcake and improve the accuracy of measurement of formation parameters, this paper presents an inversion method that can accurately calculate formation and borehole parameters and is suitable for X-ray lithology density logging. The general process of this inversion method is described below. First, a response model for broad-beam attenuation during X-ray lithology density logging is derived. Subsequently, the responses of four detectors under various formation and borehole conditions are studied by means of Monte Carlo simulation, and the energy spectra measured by each detector are divided into four energy windows (ranges) depending on the correlation with formation parameters. Finally, accurate values of formation and borehole parameters are obtained through iterative inversion using the Levenberg-Marquardt (LM) algorithm. The results of this study show that compared with previously established analysis methods, the inversion method based on forward modeling can effectively improve the accuracy of measurement of formation density and lithology index during X-ray lithology density logging, reduce the influence of the borehole environment, and overcome the deficiencies of data processing techniques based on the spine and ribs plot.

Observation of the spin Hall effect of light by a single-photon detector.

We use a single-photon detector to detect the spin Hall effect of light (SHEL) of a quasi-single-photon beam obtained in this Letter. The physics of the spin Hall effect and its quantum weak measurement method with a dimensionless pointer are elucidated through particle number representation. Our weak measurement scheme obviates the necessity of high-resolution single-photon array detectors. Consequently, we have successfully observed the spin Hall effect within a 20 ns temporal window using a position-resolution-independent single-photon detector with remarkably low-noise levels. The weak measurement of the dimensionless pointer presented in this Letter boosts both the detection accuracy and the response speed of the photonics spin Hall effect, thereby contributing significantly to fundamental theoretical research in spin photonics and precise measurements of physical property parameters.

Efficient Simulation of the Laser-Based Powder Bed Fusion Process Demonstrated on Open Lattice Materials Fabrication

Strut-based or open lattice materials are a category of advanced materials used in medical and aerospace applications due to their properties, such as high strength-to-weight ratio and energy absorption capability. The most prominent method for the fabrication of lattice materials is the Laser-based Powder Bed Fusion (L-PBF) additive manufacturing (AM) process, due to its ability to produce parts of complex geometries. The current work presents an efficient meso-scale finite element (FE) modeling methodology of the L-PBF process demonstrated in the fabrication of body-centered cubic (BCC) lattice materials. The modeling efficiency is gained through an adaptive mesh refinement technique, which results in accurate and efficient prediction of the temperature field during the process evolution. To examine the efficiency of the modeling method, the computational time is compared with that of a conventional FE simulation, based on the element and birth technique. The temperature history difference between the two approaches is minor but the adaptive mesh modeling requires only a small portion of the simulation time of the conventional model. In addition, the computational results present a good correlation with the available experimental measurements for various process parameters validating the presented efficient method.

Subnormothermic Oxygenated Machine Perfusion (24 h) in DCD Kidney Transplantation.

Ex vivo kidney perfusion is an evolving platform that demonstrates promise in preserving and rehabilitating the kidney grafts. Despite this, there is little consensus on the optimal perfusion conditions. Hypothermic perfusion offers limited functional assessment, whereas normothermic perfusion requires a more complex mechanical system and perfusate. Subnormothermic machine perfusion (SNMP) has the potential to combine the advantages of both approaches but has undergone limited investigation. Therefore, the present study sought to determine the suitability of SNMP for extended kidney preservation. SNMP at 22-25 °C was performed on a portable device for 24 h with porcine kidneys. Graft assessment included measurement of mechanical parameters and biochemical analysis of the perfusate using point-of-care tests. To investigate the viability of kidneys preserved by SNMP, porcine kidney autotransplants were performed in a donation after circulatory death (DCD) model. SNMP was also compared with static cold storage (SCS). Finally, follow-up experiments were conducted in a subset of human kidneys to test the translational significance of findings in porcine kidneys. In the perfusion-only cohort, porcine kidneys all displayed successful perfusion for 24 h by SNMP, evidenced by stable mechanical parameters and biological markers of graft function. Furthermore, in the transplant cohort, DCD grafts with 30 min of warm ischemic injury demonstrated superior posttransplant graft function when preserved by SNMP in comparison with SCS. Finally, human kidneys that underwent 24-h perfusion exhibited stable functional and biological parameters consistent with observations in porcine organs. These observations demonstrate the suitability and cross-species generalizability of subnormothermic machine perfusion to maintain stable kidney perfusion and provide foundational evidence for improved posttransplant graft function of DCD kidneys after SNMP compared with SCS.

Effects of hemorrhagic shock and rhabdomyolysis on renal microcirculation, oxygenation and function in a female swine model.

Hemorrhagic shock (HS) and rhabdomyolysis (RM) are two important risk factors of acute kidney injury (AKI) after severe trauma, however the effects of the combination of RM and HS on kidney function are unknown. The purpose of this study was to determine the impact of RM and HS on renal function, oxygenation, perfusion and morphology, in a pig model. Forty-seven female pigs were divided into 5 groups: sham, RM, HS, HS and moderate RM (RM4/HS), HS and severe RM (RM8/HS). RM was induced by intramuscular injection of Glycerol 50% with a moderate dose (4 ml/kg for RM4/HS group) or a high dose (8 ml/kg for RM and RM8/HS groups). Among animals with HS, after 90 min of hemorrhage, animals were resuscitated with fluid followed by transfusion of the withdrawn blood. Animals were followed for 48 hours. Macro and microcirculatory parameters measurements were performed. RM alone induced a decrease in creatinine clearance at 48 hours (19 (0-41) vs 102 (56-116) ml/min for RM and SHAM respectively; p = 0.0006) without alteration in renal perfusion and oxygenation. HS alone impaired temporarily renal microcirculation, function and oxygenation that were restored with fluid resuscitation. RM4/HS and RM8/HS groups induced greater impairment of renal microcirculation and function than HS alone at the end of blood spoliation that were not improved by fluid resuscitation. Mortality was increased in RM8/HS and RM4/HS groups in the first 48 hours (73% vs 56% vs 9% for RM8/HS, RM4/HS and HS groups respectively). The combination of HS and RM induced an early deleterious effect on renal microcirculation, function and oxygenation with decreased response to resuscitation and transfusion compared with HS or RM alone.

Manganese-substituted strontium ferrite catalyst on honeycomb structured cordierite support for oxidation of diesel particulate matter

Perovskite-based catalysts have been explored as low-cost substitutes for platinum (Pt)- based catalysts for diesel particulate matter (DPM) oxidation. In this work, manganese (Mn)-substituted strontium ferrite (SrFeMnO3-δ) (SFM) as a catalyst was coated on the honeycomb structure of cordierite support and tested for its catalytic performance for DPM oxidation using a real-world engine. The characteristic diffraction peaks due to the presence of the perovskite structure of SFM were observed for the cordierite-supported SFM. Mn was substituted in the lattice of un-substituted strontium ferrite and no other impurities were formed upon the Mn-substitution. Highly agglomerated SFM particles were formed solely due to the perovskite phase formation temperature (900 °C). The SFM catalyst enhanced catalytic Printex-V oxidation performance compared to its oxidation without the catalyst, where Printex V was used as the model DPM. The SFM catalyst showed high CO2 selectivity upon the oxidation of DPM. These results infer that the SFM catalyst possesses promise as an alternative to commercially available DOC catalysts based on PGM for DPM oxidation. SFM-coated cordierite support performed much better in terms of particle number, mass and surface area than commercial diesel oxidation catalyst (DOC) or without DOC at no engine load. The performance is substantially higher even at moderate engine loads of up to 40% and comparable at very high engine loads of 100%. Detailed investigations on a real engine exhaust and measurement of crucial parameters like particle number, mass and surface area suggest convincing and relatively rare evidence for its potential as a catalyst for diesel exhaust emission control catalyst.

Neural adaptive dynamic surface control for position tracking of electrohydraulic servo systems based on extended state observer

High-performance motion tracking of electro-hydraulic servo systems plays an important role in developing industrial technology. However, the system itself has parameter uncertainty, uncertain nonlinearity, and measurement noise, significantly decreasing the performance of conventional controllers designed based on nominal models. To improve the tracking performance of electro-hydraulic servo systems, an adaptive dynamic surface control method combining extended state observer and radial basis function neural network is proposed. Firstly, an extended state observer combining neural network output and parameter adaptation technology is designed without the need for speed and pressure feedback to observe the system’s unknown state variables and nonlinear matched disturbance. The design of neural networks is used to approximate mismatched disturbance with significant nonlinearity online. Then, the proposed extended state observer is introduced into the neural adaptive backstepping design, effectively compensating for simultaneous matched and mismatched disturbances, thereby suppressing most of the uncertain nonlinearity of the system. Meanwhile, online update of uncertain parameters further improves the tracking performance of the controller. In addition, the introduction of dynamic surface overcomes the “explosion of complexity” issue in backstepping design. The rigorous stability of the closed-loop system is proved by the Lyapunov stability theory. Finally, the effectiveness of the proposed controller is validated through comparative experiments on valve-controlled hydraulic cylinder.

Diurnal Variation in Choroidal Parameters Among Healthy Subjects Using Wide-Field Swept-Source Optical Coherence Tomography Angiography.

The purpose of this study was to evaluate the diurnal variation in choroidal parameters in a wide field area among healthy subjects and to identify correlations between choroidal luminal area and stromal area and various systemic factors. In this cross-sectional study, 42 eyes from 21 healthy participants (mean age = 32.4 ± 8.8 years) were examined using wide-field swept-source optical coherence tomography angiography (WF SS-OCTA, 24 mm × 20 mm). Measurements of choroidal parameters, including choroidal volume (CV), choroidal thickness (CT), choroidal vessel volume (CVV), and choroidal stromal volume (CSV), were taken at 8:00, 12:00, 18:00, and 22:00. Systemic factors, such as blood pressure and heart rate, were concurrently monitored. Our study observed significant diurnal variations in the mean total CV, CT, CVV, and CSV, with minimum measurements around 12:00 (P < 0.001) and peak values at 22:00 (P < 0.001). Furthermore, changes in CV in specific regions were more closely associated with fluctuations in CVV than CSV in the same regions. No significant diurnal variations were found in systolic (P = 0.137) or diastolic blood pressure (P = 0.236), whereas significant variations were observed in the heart rate (P = 0.001). Our study reveals diurnal variations in choroidal parameters and their associations, emphasizing that changes in choroidal volume relate more to the luminal than the stromal area in vessel-rich regions. This enhances our understanding of choroidal-related ocular diseases. Regions with higher choroidal vasculature observed greater choroidal volume changes.

Exploring pathogenesis and biomarkers through establishment of a rat model of male infertility with liver depression and kidney deficiency.

To establish a rat model that accurately replicates the clinical characteristics of male infertility (MI) with Liver Depression and Kidney Deficiency (LD & KD) and investigate the pathogenesis. After subjecting the rats to chronic restraint stress (CRS) and adenine treatment, a series of tests were conducted, including ethological assessments, evaluations of reproductive characteristics, measurements of biochemical parameters, histopathological examinations, and analyses of urinary metabolites. Additionally, bioinformatics predictions were performed for comprehensive analysis. Compared to the control, the model exhibited significant manifestations of MI with LD & KD, including reduced responsiveness, diminished frequency of capturing estrous female rats, and absence of mounting behavior. Additionally, the kidney coefficient increased markedly, while the coefficients of the testis and epididymis decreased significantly. Sperm counts and viabilities decreased notably, accompanied by an increase in sperm abnormalities. Dysregulation of reproductive hormone levels in the serum was observed, accompanied by an upregulation of proinflammatory cytokines expressions in the liver and kidney, as well as exacerbated oxidative stress in the penile corpus cavernosum and testis. The seminiferous tubules in the testis exhibited a loose arrangement, loss of germ cells, and infiltration of inflammatory cells. Furthermore, utilizing urinary metabolomics and bioinformatics analysis, 5 key biomarkers and 2 crucial targets most closely linked to MI were revealed. The study successfully established a clinically relevant animal model of MI with LD & KD. It elucidates the pathogenesis of the condition, identifies key biomarkers and targets, and provides a robust scientific foundation for the prediction, diagnosis, and treatment of MI with LD & KD.

Remote monitoring of sleep disorder using FBG sensors and FSO transmission system enabled smart vest

Optical sensors, particularly fiber Bragg grating (FBG) sensors have achieved a fast ingress into the fields of medical diagnostic and vital signs monitoring. Wearable smart textiles equipped with FBG sensors are catching huge research attention in different applications for measurement and monitoring of physiological parameters. In this paper, we report a simple technique for remote monitoring of sleep disorder using a smart vest implemented with four FBG stress sensors located at different sides of the vest and free space optics (FSO) transmission system. The sleep disorder of the patient is monitored in real time through shifts in the original Bragg wavelengths of sensors by stress loading during random changes in patient’s sleeping postures. The reflected wavelength from a stress loaded sensor at a certain posture is transmitted over 0.5 km long FSO channel towards remote medical center, photodetected, and then can be processed in a PC to record the restlessness in a certain time interval in terms of total number of times sleeping postures are changed, total time spent at a certain posture etc. To correctly detect the stress loaded FBG sensor at the medical center, various parameters of FBG sensors and demultiplexer are carefully adjusted to minimize the power leakages from unloaded sensors that may result into errors in the detection. Maximum dynamic range around 45 dB has been achieved ensuring accurate detection. This study not only provides a cost-efficient and non-intrusive solution for monitoring the sleep disorder of patients but also can be used for real-time monitoring of various other ailments, such as lung, brain, and cardiac diseases in future.

Organ Segmentation and Phenotypic Trait Extraction of Cotton Seedling Point Clouds Based on a 3D Lightweight Network

Cotton is an important economic crop; therefore, enhancing cotton yield and cultivating superior varieties are key research priorities. The seedling stage, a critical phase in cotton production, significantly influences the subsequent growth and yield of the crop. Therefore, breeding experts often choose to measure phenotypic parameters during this period to make breeding decisions. Traditional methods of phenotypic parameter measurement require manual processes, which are not only tedious and inefficient but can also damage the plants. To effectively, rapidly, and accurately extract three-dimensional phenotypic parameters of cotton seedlings, precise segmentation of phenotypic organs must first be achieved. This paper proposes a neural network-based segmentation algorithm for cotton seedling organs, which, compared to the average precision of 75.4% in traditional unsupervised learning, achieves an average precision of 96.67%, demonstrating excellent segmentation performance. The segmented leaf and stem point clouds are used for the calculation of phenotypic parameters such as stem length, leaf length, leaf width, and leaf area. Comparisons with actual measurements yield coefficients of determination R2 of 91.97%, 90.97%, 92.72%, and 95.44%, respectively. The results indicate that the algorithm proposed in this paper can achieve precise segmentation of stem and leaf organs, and can efficiently and accurately extract three-dimensional phenotypic structural information of cotton seedlings. In summary, this study not only made significant progress in the precise segmentation of cotton seedling organs and the extraction of three-dimensional phenotypic structural information, but the algorithm also demonstrates strong applicability to different varieties of cotton seedlings. This provides new perspectives and methods for plant researchers and breeding experts, contributing to the advancement of the plant phenotypic computation field and bringing new breakthroughs and opportunities to the field of plant science research.

Investigation of flashover occurrence criterion based on thermal equilibrium theory

Flashover is the rapid transition to a state of total surface involvement in a fire of combustible material within an enclosure fire, which is the most serious and fatal event in building fires. Although previous studies have provided quantitative and qualitative standards for flashover, the criteria of flashover were normally based on the independent measurement of experimental parameters and phenomena rather than the underlying physical reasons, resulting in a lack of mutual relationships between these criteria and the inability to reflect physical mechanisms. Moreover, the flashover criteria vary for different compartment fire fuels, which directly affects the calculation of compartment fire theory. This work was performed to provide a unified principle on the criteria of flashover based on the thermal equilibrium theory. The critical conditions for flashover are quantitatively developed by establishing a partial differential equation for the energy generation rate and energy loss rate with respect to the temperature inside the compartment. Moreover, based on the partial differential equation, inequalities were established for the relationship between the temperature of the hot gas and the heat flux of the floor at the onset of flashover, which was validated by the compartment experiment data. It was found that due to differences in emissivity and net heat transfer rate, at the onset of flashover, the hot gas temperature and the radiation heat flux at the floor were different for different fuels, and a high hot gas temperature does not necessarily indicate a high radiation heat flux at the floor.

A New Method for Anti-Interference Measurement of Capacitance Parameters of Long-Distance Transmission Lines Based on Harmonic Components

In the context of strong electromagnetic interference environments, the measurement accuracy of the capacitance parameters of transmission lines under power frequency measurement methods is not high. In this paper, a capacitance parameter anti-interference measurement method for transmission lines based on harmonic components is proposed to overcome the impact of power frequency interference. When applying this method, it is first necessary to open-circuit the end of the line under test. Subsequently, apply voltage to the head end of the tested line through a step-up transformer. Due to the saturation of the transformer during no-load conditions, a large number of harmonics are generated, primarily third harmonic. The third harmonic components of voltage and current on the tested transmission line are extracted using the Fourier transform. The proposed method addresses the influence of line distribution effects by establishing a distributed parameter model for long-distance transmission lines. The relevant transmission matrix for the zero-sequence distributed parameters is obtained by combining Laplace transform and similarity transform to solve the transmission line equations. Using synchronous measurement data from the third harmonic components of voltage and current at both ends of the transmission line, combined with the transmission matrix, this method accurately measures the zero-sequence capacitance parameters. The PSCAD/EMTDC simulation results and field test outcomes have demonstrated the feasibility and accuracy of the proposed method for measuring line capacitance parameters under strong electromagnetic interference.

Ultrasonic mode conversion for in-line foam structure measurement in highly aerated batters using machine learning

An ultrasonic-based method was developed to enable in-line measurements of foam structure parameters for highly aerated batters by mode conversion. Biscuit batters were foamed to different degrees (density: 364–922 g/L) by varying the mixing head speed and pressure. Density and foam structure changes were detected by efficient offline analytics (nref measurement = 96). Ultrasonic signal data were recorded using two ultrasonic sensors attached to an industry-standard tube. Mode conversion effects in the ultrasonic signals were obtained to predict the rheological parameters of the batters. The frequency range in which surface waves are expected was particularly suitable for detecting rheological changes in highly aerated batters. An ultrasonic-based, online-capable method for process monitoring was implemented and established regarding feature selection in combination with machine learning and 5-fold cross-validation. The developed ultrasonic sensor system shows high accuracy for online density measurement (R2 = 0.98) and offers decent accuracy for measurements of foam structure parameters (Bubble count: R2 = 0.95, Relative span: R2 = 0.93, Sauter diameter: R2 = 0.83). The main benefit of this novel technique is that integrating ultrasonic signal features based on mode conversion leads to a robust foam structure analysis, which has the advantage of being retrofitable into existing processes.

Accuracy of soy-based resins for dental 3D printing

ABSTRACT Objectives To verify the accuracy of soy-based resins for dental three-dimensional (3D) printing. Materials and Methods After conducting a power analysis, models of 10 consecutively treated patients were produced from four different resins using a dental 3D printer. Two of these resins were soy based and therefore biodegradable. These 20 models were measured manually with a caliper as well as digitally by software and compared based on measurement parameters in all three spatial axes. Results No statistically significant differences were found between the four different resins or between the manual and digital measurements. Conclusions Soy-based resin seems to be a suitable material for orthodontic 3D printing and is a more environmentally friendly alternative to conventional dental resins. Digital model analysis seems to produce comparable results to manual measurement.

Precision Regulation and Forecasting of Greenhouse Tomato Growth Conditions Using an Improved GA-BP Model

Tomatoes are annual herbaceous plants of the family Solanaceae. They have very stringent requirements for their growing environment and climate conditions. To precisely control the greenhouse environment for tomato growth, this project designed and implemented a monitoring system utilizing programmable logic controllers and a data acquisition system for monitoring. Sensors are installed at key locations in the greenhouse, such as near the ground, in the plant canopy, and under the roof, to monitor environmental parameters such as temperature, humidity, light intensity, and carbon dioxide concentration in real time. A three-layer feedforward GA-BP neural network model was established using soil temperature, soil humidity, air humidity, and illumination as predictive parameters. This technology predicts optimal environmental parameters and performs real-time monitoring and intelligent control, overcoming the traditional BP neural network’s drawbacks of slow convergence, susceptibility to disturbance, and poor generalization ability, with the current model’s average prediction error being less than 5%. It provides a theoretical basis and decision support for precision control and related environmental forecasting in agricultural projects. Based on the growth characteristics, physiological and morphological features of tomatoes, and the comprehensive impact of planting conditions, the technology enhances tomato yield and quality while reducing production costs and labor inputs. It mainly includes the establishment of tomato growth models, measurement and control of environmental parameters, and the design and optimization of intelligent decision control systems. Research outcomes in this field are significant for improving agricultural production efficiency, ensuring food security, and promoting sustainable agricultural development.